engleski

The influence of circular sample plot sizes on volume estimates of a selection stand

Stand volume estimate is based on data from sample plots. The aim of this research was to compare stand volume estimates based on a systematic sample of circular plots with different radii. By this, influence of plot size on volume estimate and efficiency of stand measurement was also indirectly assessed. Measurements were conducted in a beech-fir selection stand situated in the Educational and Experimental Forest Site "Zalesina" in the region of Gorski Kotar in Croatia. Tree diameters at breast height (DBH) were measured in a systematic sample of 16 concentric circular sample plots. Tree location from the plot centre was recorded with the azimuth and distance. All the trees with DBH of 10 cm or more were measured in the plot with a 13 meter radius, and the trees with DBH 30 cm and more were measured in the plot with a 19 m radius and the trees with DBH of 50 cm and more were measured in the plot with a 26 m radius. The computer programme CirCon was developed to calculate the stand volume based on measured and simulated plots (the radii were different from the measured ones). The plots based on real measurements were simulated according to the ones used in the forest management practice (singular and concentric circle plots). We simulated 7 methods: K1-12 (12.62 m radius plot) ; K2-5.12 (concentric circle plot with radii of 5 and 12 m) ; K2-7, 14 ; K2-10, 15 ; K2-12, 16 ; K2-13, 19 ; and K3-13, 19, 26 (three concentric circles with radii of 13, 19 and 26 m). The calculated volume estimates on the same standing points differed from method to method depending on spatial tree distribution and plot size. There was no statistical difference in the total volume among the analysed methods (repeated measurements ANOVA: F=1.31, df=6, p=0.259). We compared the similarity of the analysed methods using Cluster analysis. Three clusters were sorted out: C1=(K1-12 ; K2-5, 12), C2=(K2-7, 14 ; K2-10, 15 ; K2-12, 16), and C3=(K2-13, 19 ; K3-13, 19, 26). In order to distinguish the methods within the clusters, we compared relative precisions (SE/mean• t0, 05) for a 95% confidence interval. In C1, precision was about 18%, in C2 it ranged from 17.19% to 19.93%, while precision was best in C3. For K2-13, 19 precision was 12.57% and for K3-13, 19, 26 it was 10.47%. The choice of a measurement method should be governed by the cost of measurements and the expected precision.

forest inventory; circular sample plots; volume estimation; precision; computer model

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